Day 19.
This commit is contained in:
Mikaël Capelle
parent
ddebd26db2
commit
7f4a34b2d7
458
2022/day19.py
458
2022/day19.py
@ -1,17 +1,14 @@
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# -*- encoding: utf-8 -*-
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import heapq
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import math
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import sys
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import time
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from collections import defaultdict
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from typing import Literal, TypedDict
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from typing import Literal
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import numpy as np
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import parse
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from tqdm import tqdm
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Reagent = Literal["ore", "clay", "obsidian", "geode"]
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REAGENTS: tuple[Reagent] = (
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REAGENTS: tuple[Reagent, ...] = (
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"ore",
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"clay",
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"obsidian",
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@ -20,23 +17,6 @@ REAGENTS: tuple[Reagent] = (
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IntOfReagent = dict[Reagent, int]
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lines = sys.stdin.read().splitlines()
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blueprints: list[dict[Reagent, IntOfReagent]] = [
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{
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"ore": {"ore": 4},
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"clay": {"ore": 2},
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"obsidian": {"ore": 3, "clay": 14},
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"geode": {"ore": 2, "obsidian": 7},
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},
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{
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"ore": {"ore": 2},
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"clay": {"ore": 3},
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"obsidian": {"ore": 3, "clay": 8},
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"geode": {"ore": 3, "obsidian": 12},
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},
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]
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class State:
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robots: IntOfReagent
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@ -64,11 +44,6 @@ class State:
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and self.reagents == other.reagents
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)
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def __lt__(self, other) -> bool:
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return isinstance(other, State) and tuple(
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(self.robots[r], self.reagents[r]) for r in REAGENTS
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) > tuple((other.robots[r], other.reagents[r]) for r in REAGENTS)
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def __hash__(self) -> int:
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return hash(tuple((self.robots[r], self.reagents[r]) for r in REAGENTS))
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@ -89,245 +64,45 @@ def dominates(lhs: State, rhs: State):
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)
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MAX_TIME = 24
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blueprint = blueprints[1]
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lines = sys.stdin.read().splitlines()
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# parents: dict[State, tuple[State | None, int]] = {State(): (None, 0)}
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# queue = [(0, State())]
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# visited: set[State] = set()
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# at_time: dict[int, list[State]] = defaultdict(lambda: [])
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blueprints: list[dict[Reagent, IntOfReagent]] = []
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for line in lines:
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r = parse.parse(
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"Blueprint {}: "
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"Each ore robot costs {:d} ore. "
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"Each clay robot costs {:d} ore. "
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"Each obsidian robot costs {:d} ore and {:d} clay. "
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"Each geode robot costs {:d} ore and {:d} obsidian.",
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line,
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)
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# while queue:
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# time, state = heapq.heappop(queue)
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# if state in visited:
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# continue
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# print(time, state)
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# visited.add(state)
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# at_time[time].append(state)
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# if time > MAX_TIME:
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# continue
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# if len(queue) % 200 == 0:
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# print(len(queue), len(visited), time)
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# can_build_any: bool = False
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# for reagent in REAGENTS:
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# needed = blueprint[reagent]
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# if any(state.robots[r] == 0 for r in needed):
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# continue
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# time_to_complete = max(
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# max(
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# math.ceil((needed[r] - state.reagents[r]) / state.robots[r])
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# for r in needed
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# ),
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# 0,
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# )
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# # if time_to_complete != 0:
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# # continue
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# if time + time_to_complete + 1 > MAX_TIME:
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# continue
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# wait = time_to_complete + 1
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# reagents = {
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# r: state.reagents[r] + wait * state.robots[r] - needed.get(r, 0)
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# for r in REAGENTS
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# }
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# robots = state.robots.copy()
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# robots[reagent] += 1
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# state_2 = State(reagents=reagents, robots=robots)
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# if state_2 in visited:
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# continue
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# if any(dominates(state_v, state_2) for state_v in at_time[time + wait]):
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# continue
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# # print(time + wait)
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# # if any(dominates(state_3, state_2) for state_3 in at_time[time + wait]):
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# # print("?")
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# # continue
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# if state_2 not in parents or parents[state_2][1] > time + wait:
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# parents[state_2] = (state, time + wait)
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# heapq.heappush(queue, (time + wait, state_2))
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# can_build_any = True
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# at_time[time + wait].append(state_2)
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# if not can_build_any:
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# state_2 = State(
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# reagents={
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# r: state.reagents[r] + state.robots[r] * (MAX_TIME - time)
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# for r in REAGENTS
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# },
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# robots=state.robots,
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# )
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# if state_2 in visited:
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# continue
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# if state_2 not in parents or parents[state_2][1] > time + wait:
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# parents[state_2] = (state, MAX_TIME)
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# heapq.heappush(queue, (MAX_TIME, state_2))
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# print(len(visited))
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# print(max(state.reagents["geode"] for state in visited))
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# exit()
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# while states:
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# state = states.pop()
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# processed.append(state)
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# if state.time > MAX_TIME:
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# continue
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# if len(states) % 100 == 0:
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# print(len(states), len(processed), min((s.time for s in states), default=1))
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# can_build_any: bool = False
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# for reagent in REAGENTS:
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# needed = blueprint[reagent]
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# if any(state.robots[r] == 0 for r in needed):
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# continue
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# time_to_complete = max(
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# max(
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# math.ceil((needed[r] - state.reagents[r]) / state.robots[r])
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# for r in needed
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# ),
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# 0,
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# )
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# if state.time + time_to_complete + 1 > MAX_TIME:
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# continue
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# wait = time_to_complete + 1
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# reagents = {
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# r: state.reagents[r] + wait * state.robots[r] - needed.get(r, 0)
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# for r in REAGENTS
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# }
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# robots = state.robots.copy()
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# robots[reagent] += 1
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# can_build_any = True
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# state_2 = State(time=state.time + wait, reagents=reagents, robots=robots)
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# # print(f"{state} -> {state_2}")
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# states.add(state_2)
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# if not any(dominates(s2, state_2) for s2 in states):
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# states.add(state)
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# # print(f"can build {reagent} in {time_to_complete}")
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# if not can_build_any:
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# states.add(
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# State(
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# time=MAX_TIME + 1,
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# reagents={
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# r: state.reagents[r] + state.robots[r] * (MAX_TIME - state.time)
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# for r in REAGENTS
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# },
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# robots=state.robots,
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# )
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# )
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# if len(states) % 1000 == 0:
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# print("filtering")
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# states = {
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# s1
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# for s1 in states
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# if not any(dominates(s2, s1) for s2 in states if s2 is not s1)
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# }
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# # if len(states) > 4:
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# # break
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# # break
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# print(len(processed))
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# print(max(state.reagents["geode"] for state in processed))
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# exit()
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# for t in range(1, 25):
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# states = set()
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# for state in state_after_t[t - 1]:
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# robots_that_can_be_built = [
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# robot
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# for robot in REAGENTS
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# if all(
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# state.reagents[reagent] >= blueprint[robot].get(reagent, 0)
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# for reagent in REAGENTS
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# )
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# ]
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# new_states = set()
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# # new reagents
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# reagents = {
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# reagent: state.reagents[reagent] + state.robots[reagent]
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# for reagent in REAGENTS
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# }
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# # if we can build anything, there is no point in waiting
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# if len(robots_that_can_be_built) != len(REAGENTS):
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# new_states.add(State(robots=state.robots, reagents=reagents))
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# for robot in robots_that_can_be_built:
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# robots = state.robots.copy()
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# robots[robot] += 1
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# reagents = {
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# reagent: state.reagents[reagent]
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# + state.robots[reagent]
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# - blueprint[robot].get(reagent, 0)
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# for reagent in REAGENTS
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# }
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# new_states.add(State(robots=robots, reagents=reagents))
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# new_states = [
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# s1
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# for s1 in new_states
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# if not any(s1 is not s2 and dominates(s2, s1) for s2 in new_states)
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# ]
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# states = {
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# s1 for s1 in states if not any(dominates(s2, s1) for s2 in new_states)
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# }
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# states.update(new_states)
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# state_after_t[t] = states
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# exit()
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blueprints.append(
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{
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"ore": {"ore": r[1]},
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"clay": {"ore": r[2]},
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"obsidian": {"ore": r[3], "clay": r[4]},
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"geode": {"ore": r[5], "obsidian": r[6]},
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}
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)
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MAX_TIME = 24
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blueprint = blueprints[0]
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def run(blueprint: dict[Reagent, dict[Reagent, int]], max_time: int) -> int:
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state_after_t: dict[int, list[State]] = {0: [State()]}
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# since we can only build one robot per time, we do not need more than X robots
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# of type K where X is the maximum number of K required among all robots, e.g.,
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# in the first toy blueprint, we need at most 4 ore robots, 14 clay ones and 7
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# obsidian ones
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maximums = {
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name: max(blueprint[r].get(name, 0) for r in REAGENTS) for name in REAGENTS
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}
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for t in range(1, 25):
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print(t, len(state_after_t[t - 1]))
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state_after_t: dict[int, set[State]] = {0: [State()]}
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bests_for_robots: dict[tuple[int, ...], list[State]] = {}
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bests_for_reagents: dict[tuple[int, ...], list[State]] = {}
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for t in range(1, max_time + 1):
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state_after_t[t] = []
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t1 = time.time()
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# list of new states at the end of step t that we are going to prune later
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states_for_t: set[State] = set()
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for state in state_after_t[t - 1]:
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robots_that_can_be_built = [
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@ -339,17 +114,25 @@ for t in range(1, 25):
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)
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]
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# print(t, robots_that_can_be_built)
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new_states: set[State] = set()
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# new reagents
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reagents = {
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states_for_t.add(
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State(
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robots=state.robots,
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reagents={
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reagent: state.reagents[reagent] + state.robots[reagent]
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for reagent in REAGENTS
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}
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},
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)
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)
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# if we can build anything, there is no point in waiting
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new_states.add(State(robots=state.robots, reagents=reagents))
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# this speeds-up the process and work but I am not 100% sure this is right
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if "geode" in robots_that_can_be_built:
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robots_that_can_be_built = ["geode"]
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else:
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robots_that_can_be_built = [
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robot
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for robot in robots_that_can_be_built
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if state.robots[robot] < maximums[robot]
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]
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for robot in robots_that_can_be_built:
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robots = state.robots.copy()
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@ -360,128 +143,45 @@ for t in range(1, 25):
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- blueprint[robot].get(reagent, 0)
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for reagent in REAGENTS
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}
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new_states.add(State(robots=robots, reagents=reagents))
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for s1 in new_states:
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r1 = tuple(s1.robots[r] for r in REAGENTS)
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if r1 not in bests_for_robots:
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bests_for_robots[r1] = [s1]
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else:
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is_dominated = False
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for s2 in bests_for_robots[r1]:
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if all(s2.reagents[r] >= s1.reagents[r] for r in REAGENTS):
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is_dominated = True
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break
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if not is_dominated:
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bests_for_robots[r1].append(s1)
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r2 = tuple(s1.reagents[r] for r in REAGENTS)
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if r2 not in bests_for_reagents:
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bests_for_reagents[r2] = [s1]
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else:
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is_dominated = False
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for s2 in bests_for_reagents[r2]:
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if all(s2.robots[r] >= s1.robots[r] for r in REAGENTS):
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is_dominated = True
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break
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if not is_dominated:
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bests_for_reagents[r2].append(s1)
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# state_after_t[t].extend(new_states)
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t2 = time.time()
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for bests in bests_for_robots.values():
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dominated = [False for _ in range(len(bests))]
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for i_s1, s1 in enumerate(bests):
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if dominated[i_s1]:
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continue
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for i_s2, s2 in enumerate(bests[i_s1 + 1 :], start=i_s1 + 1):
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if dominated[i_s2]:
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continue
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if all(s1.reagents[r] >= s2.reagents[r] for r in REAGENTS):
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dominated[i_s2] = True
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state_after_t[t].extend(
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s1 for i_s1, s1 in enumerate(bests) if not dominated[i_s1]
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)
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for bests in bests_for_reagents.values():
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dominated = [False for _ in range(len(bests))]
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for i_s1, s1 in enumerate(bests):
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if dominated[i_s1]:
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continue
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for i_s2, s2 in enumerate(bests[i_s1 + 1 :], start=i_s1 + 1):
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if dominated[i_s2]:
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continue
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if all(s1.robots[r] >= s2.robots[r] for r in REAGENTS):
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dominated[i_s2] = True
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state_after_t[t].extend(
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s1 for i_s1, s1 in enumerate(bests) if not dominated[i_s1]
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)
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t3 = time.time()
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states_for_t.add(State(robots=robots, reagents=reagents))
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# use numpy to switch computation of dominated states -> store each state
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# as a 8 array and use numpy broadcasting to find dominated states
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states_after = np.asarray(list(states_for_t))
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np_states = np.array(
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[
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[state.robots[r] for r in REAGENTS] + [state.reagents[r] for r in REAGENTS]
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for state in state_after_t[t]
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[state.robots[r] for r in REAGENTS]
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+ [state.reagents[r] for r in REAGENTS]
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for state in states_after
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]
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)
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dominated = np.zeros(len(np_states), dtype=bool)
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t4 = time.time()
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to_keep = []
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while len(np_states) > 0:
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first_dom = (np_states[1:] >= np_states[0]).all(axis=1).any()
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# c = (np_states[None, :, :] <= np_states[:, None, :]).all(axis=-1)
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# c[np.arange(len(np_states)), np.arange(len(np_states))] = False
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# dominated = c.any(axis=0)
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if first_dom:
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np_states = np_states[1:]
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else:
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to_keep.append(np_states[0])
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np_states = np_states[1:][~(np_states[1:] <= np_states[0]).all(axis=1)]
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for i in range(len(np_states)):
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if dominated[i]:
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continue
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dominated[i] = not (np_states[i + 1 :] <= np_states[i]).any(axis=1)
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dominated[i + 1 :] = (np_states[i + 1 :] <= np_states[i]).all(axis=1)
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t5 = time.time()
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state_after_t[t] = list(np.array(state_after_t[t])[~dominated])
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t6 = time.time()
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print(
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"->",
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t,
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len(state_after_t[t]),
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||||
dominated.sum(),
|
||||
t2 - t1,
|
||||
t3 - t2,
|
||||
t4 - t3,
|
||||
t5 - t4,
|
||||
t6 - t5,
|
||||
state_after_t[t] = {
|
||||
State(
|
||||
robots=dict(zip(REAGENTS, row[:4])),
|
||||
reagents=dict(zip(REAGENTS, row[4:])),
|
||||
)
|
||||
for row in to_keep
|
||||
}
|
||||
|
||||
# print("->", len(state_after_t[t]))
|
||||
return max(state.reagents["geode"] for state in state_after_t[max_time])
|
||||
|
||||
# dominated = [False for _ in range(len(state_after_t[t]))]
|
||||
# keep = set()
|
||||
# for i_s1, s1 in enumerate(tqdm(state_after_t[t])):
|
||||
# if dominated[i_s1]:
|
||||
# continue
|
||||
# for i_s2, s2 in enumerate(state_after_t[t][i_s1 + 1 :], start=i_s1 + 1):
|
||||
# if dominated[i_s2]:
|
||||
# continue
|
||||
|
||||
# if dominates(s1, s2):
|
||||
# dominated[i_s2] = True
|
||||
# elif dominates(s2, s1):
|
||||
# dominated[i_s1] = True
|
||||
# break
|
||||
answer_1 = sum(
|
||||
(i_blueprint + 1) * run(blueprint, 24)
|
||||
for i_blueprint, blueprint in enumerate(tqdm(blueprints))
|
||||
)
|
||||
print(f"answer 1 is {answer_1}")
|
||||
|
||||
# if not dominated[i_s1]:
|
||||
# keep.add(s1)
|
||||
|
||||
# state_after_t[t] = list(keep)
|
||||
|
||||
# print(len(state_after_t[t]))
|
||||
# print(sum(dominated))
|
||||
# break
|
||||
|
||||
print(max(state.reagents["geode"] for state in state_after_t[24]))
|
||||
answer_2 = run(blueprints[0], 32) * run(blueprints[1], 32) * run(blueprints[2], 32)
|
||||
print(f"answer 2 is {answer_2}")
|
||||
|
||||
30
2022/inputs/day19.txt
Normal file
30
2022/inputs/day19.txt
Normal file
@ -0,0 +1,30 @@
|
||||
Blueprint 1: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 12 clay. Each geode robot costs 4 ore and 19 obsidian.
|
||||
Blueprint 2: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 11 clay. Each geode robot costs 2 ore and 7 obsidian.
|
||||
Blueprint 3: Each ore robot costs 3 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 13 clay. Each geode robot costs 3 ore and 12 obsidian.
|
||||
Blueprint 4: Each ore robot costs 2 ore. Each clay robot costs 3 ore. Each obsidian robot costs 3 ore and 18 clay. Each geode robot costs 2 ore and 19 obsidian.
|
||||
Blueprint 5: Each ore robot costs 2 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 19 clay. Each geode robot costs 4 ore and 13 obsidian.
|
||||
Blueprint 6: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 7 clay. Each geode robot costs 4 ore and 11 obsidian.
|
||||
Blueprint 7: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 15 clay. Each geode robot costs 4 ore and 17 obsidian.
|
||||
Blueprint 8: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 13 clay. Each geode robot costs 3 ore and 7 obsidian.
|
||||
Blueprint 9: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 12 clay. Each geode robot costs 3 ore and 15 obsidian.
|
||||
Blueprint 10: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 4 ore and 18 clay. Each geode robot costs 4 ore and 11 obsidian.
|
||||
Blueprint 11: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 8 clay. Each geode robot costs 2 ore and 15 obsidian.
|
||||
Blueprint 12: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 4 ore and 8 clay. Each geode robot costs 3 ore and 7 obsidian.
|
||||
Blueprint 13: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 3 ore and 10 clay. Each geode robot costs 2 ore and 10 obsidian.
|
||||
Blueprint 14: Each ore robot costs 2 ore. Each clay robot costs 3 ore. Each obsidian robot costs 3 ore and 13 clay. Each geode robot costs 2 ore and 20 obsidian.
|
||||
Blueprint 15: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 19 clay. Each geode robot costs 3 ore and 8 obsidian.
|
||||
Blueprint 16: Each ore robot costs 3 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 16 clay. Each geode robot costs 2 ore and 18 obsidian.
|
||||
Blueprint 17: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 9 clay. Each geode robot costs 3 ore and 19 obsidian.
|
||||
Blueprint 18: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 11 clay. Each geode robot costs 4 ore and 8 obsidian.
|
||||
Blueprint 19: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 12 clay. Each geode robot costs 3 ore and 17 obsidian.
|
||||
Blueprint 20: Each ore robot costs 3 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 14 clay. Each geode robot costs 3 ore and 17 obsidian.
|
||||
Blueprint 21: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 15 clay. Each geode robot costs 3 ore and 16 obsidian.
|
||||
Blueprint 22: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 16 clay. Each geode robot costs 4 ore and 16 obsidian.
|
||||
Blueprint 23: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 19 clay. Each geode robot costs 4 ore and 11 obsidian.
|
||||
Blueprint 24: Each ore robot costs 4 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 18 clay. Each geode robot costs 4 ore and 9 obsidian.
|
||||
Blueprint 25: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 2 ore and 17 clay. Each geode robot costs 3 ore and 16 obsidian.
|
||||
Blueprint 26: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 2 ore and 20 clay. Each geode robot costs 4 ore and 7 obsidian.
|
||||
Blueprint 27: Each ore robot costs 2 ore. Each clay robot costs 2 ore. Each obsidian robot costs 2 ore and 8 clay. Each geode robot costs 2 ore and 14 obsidian.
|
||||
Blueprint 28: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 3 ore and 20 clay. Each geode robot costs 3 ore and 14 obsidian.
|
||||
Blueprint 29: Each ore robot costs 4 ore. Each clay robot costs 3 ore. Each obsidian robot costs 4 ore and 20 clay. Each geode robot costs 4 ore and 8 obsidian.
|
||||
Blueprint 30: Each ore robot costs 3 ore. Each clay robot costs 4 ore. Each obsidian robot costs 4 ore and 18 clay. Each geode robot costs 3 ore and 13 obsidian.
|
||||
Loading…
Reference in New Issue
Block a user